There’s a lot to unpack here, and I appreciate you raising it. The tone of posts like this can drift into alarmism, but underneath that anxiety are legitimate questions about ethics, governance, trust, and transparency. What we’re seeing isn’t AI “disappearing” or becoming weaker. We’re seeing the natural evolution of a powerful technology entering a stage of accountability. Every major platform built its business on content discovery, attention, and trust. When misinformation, synthetic content, or deepfakes start driving engagement at scale, it threatens that trust. So companies are reacting the same way financial institutions, aviation, pharmaceuticals, and cybersecurity industries eventually had to: by putting guardrails in place. This isn’t the beginning of the end. It’s the beginning of maturity. A few key realities are worth noting: • Platforms aren't banning AI. They’re requiring transparency in how it’s used, especially when the content could manipulate public perception, mislead audiences, or fabricate reality. • Regulation and platform policies will not eliminate creativity, but they will differentiate responsible use from irresponsible exploitation. • Restrictions today always lead to breakthroughs tomorrow. When constraints are introduced, innovation improves. This is how technologies evolve from novelty into infrastructure. • The market will move toward tools and creators that are verifiable, ethical, and aligned with real value, not those chasing clicks or exploiting ambiguity. And yes, there will be turbulence. Features will tighten. Capabilities will change. Some people will lose monetization or reach if they relied on deception. Others will build stronger brands because trust will become a competitive advantage. The bigger shift isn’t the technology. It’s the expectation. We’re moving from: “Look what AI can make” to “Can I trust what I’m consuming and who created it?” That is uncomfortable for some, but healthy for the ecosystem. So instead of seeing this as restriction, we can see it as refinement. The tools will continue to improve. The policies will continue to evolve. And the next generation of AI experiences will likely be more transparent, more aligned with real-world value, and less dependent on shock and spectacle.

This hit a nerve in the best way. We are in a moment where complexity is being mistaken for capability. Flashy workflows, stacked agents, and animated dashboards feel impressive, but they often mask a missing foundation: a clearly defined problem worth solving. In every meaningful AI deployment I’ve seen, success didn’t come from how complicated the system looked. It came from clarity. Clarity of the workflow. Clarity of the bottleneck. Clarity of the outcome. And simplicity is not a lack of sophistication. It is the result of understanding. Organizations do not scale because someone built a 47-node automation that generates engagement on LinkedIn. They scale because leaders took the time to understand what was broken, what mattered, and what could be improved with the least friction. AI isn’t supposed to be a spectacle. It is supposed to be useful. It is supposed to reduce cognitive load, not create new operational debt. The flashiest systems will always get applause. The simplest systems will always get adoption. So before building the next “look what I made” workflow, we should be asking: - What pain point does this remove? - Is this the most straightforward path to value? - Will the people responsible for using it understand it? - And if no one applauded it publicly, would it still be worth building? Because the real test isn’t likes, impressions, or fire emojis. It’s whether the business runs better after implementation. AI isn’t the problem. Alignment is.

@Rondon Sarnik, currently, I would not use Replit at all, as their security is not where I feel comfortable, especially given the loss of their clients' data.

@Virginia Earl, I'm not in the Bootcamp, so I cannot comment on that, other than to say that I am not surprised, based on my experience during the AI Advantage Summit and my discoveries during my research for my dissertation.